{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from config import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(f'{year}年{month}月')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sys\n",
    "sys.path.append('../../py')\n",
    "import db\n",
    "import weighted\n",
    "import inspect\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as stats\n",
    "import numpy as np\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_original=pd.read_sql(sql=f\"select * from _{year}{month:02} where monthly_salary>0 and monthly_salary<80000\", con=db.get_conn())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(78009, 94)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_original.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data_original"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "del data['publish_date']\n",
    "del data['published_on_weekend']\n",
    "del data['title']\n",
    "del data['company_title']\n",
    "del data['company_description']\n",
    "del data['job_description']\n",
    "del data['job_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_sub_stats_by_prefix(data, prefix):\n",
    "    \n",
    "    features = [feature for feature in data.columns if feature.startswith(prefix)]\n",
    "    salary_mean=[]\n",
    "    salary_median=[]\n",
    "    salary_95_min=[]\n",
    "    salary_95_max=[]\n",
    "    count=[]\n",
    "    \n",
    "    features_out=[]\n",
    "    for feature in features:\n",
    "        #print(feature)\n",
    "        idata=data[data[feature]==1]\n",
    "        headcount=idata.headcount.sum()\n",
    "        values = idata.monthly_salary.values\n",
    "        weights = idata.headcount.values\n",
    "        #print(str(headcount))\n",
    "        if headcount==0:\n",
    "            continue\n",
    "        \n",
    "        salary_mean.append(weighted.weighted_mean(values, weights))\n",
    "        q = weighted.weighted_quantile(values,[0.025,0.5,0.975],weights)\n",
    "        salary_median.append(q[1])\n",
    "        salary_95_min.append(q[0])\n",
    "        salary_95_max.append(q[2])\n",
    "        count.append(idata.headcount.sum())\n",
    "        features_out.append(feature)\n",
    "    sub_data=pd.DataFrame()\n",
    "    sub_data['rank']=range(0,len(features_out))\n",
    "    sub_data[prefix]=[f.replace(prefix,'') for f in features_out]\n",
    "    sub_data['salary_mean']=salary_mean\n",
    "    sub_data['salary_median']=salary_median\n",
    "    sub_data['salary_95_min']=salary_95_min\n",
    "    sub_data['salary_95_max']=salary_95_max\n",
    "    sub_data['head_count']=count\n",
    "    sub_data['percentage']=count/np.sum(count)\n",
    "    sub_data=sub_data.sort_values(by='salary_mean', ascending=False)\n",
    "    sub_data['rank']=range(1,len(features_out)+1)\n",
    "    #sub_data=sub_data.reset_index()\n",
    "    return sub_data\n",
    "\n",
    "def apply_style(sub_data):\n",
    "    return sub_data.style.hide_index().format(\n",
    "        {\"percentage\":\"{:.2%}\",\"salary_mean\":\"{:.0f}\",\"salary_median\":\"{:.0f}\",\"salary_95_min\":\"{:.0f}\",\"salary_95_max\":\"{:.0f}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_pl=get_sub_stats_by_prefix(data,'pl_')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_56e7a924_3380_11ea_af77_701ce71031ef\" ><thead>    <tr>        <th class=\"col_heading level0 col0\" >rank</th>        <th class=\"col_heading level0 col1\" >pl_</th>        <th class=\"col_heading level0 col2\" >salary_mean</th>        <th class=\"col_heading level0 col3\" >salary_median</th>        <th class=\"col_heading level0 col4\" >salary_95_min</th>        <th class=\"col_heading level0 col5\" >salary_95_max</th>        <th class=\"col_heading level0 col6\" >head_count</th>        <th class=\"col_heading level0 col7\" >percentage</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col1\" class=\"data row0 col1\" >rust</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col2\" class=\"data row0 col2\" >20713</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col3\" class=\"data row0 col3\" >17500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col4\" class=\"data row0 col4\" >5042</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col5\" class=\"data row0 col5\" >46250</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col6\" class=\"data row0 col6\" >480</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow0_col7\" class=\"data row0 col7\" >0.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col0\" class=\"data row1 col0\" >2</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col1\" class=\"data row1 col1\" >typescript</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col2\" class=\"data row1 col2\" >18503</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col3\" class=\"data row1 col3\" >22500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col4\" class=\"data row1 col4\" >6000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col5\" class=\"data row1 col5\" >30000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col6\" class=\"data row1 col6\" >1821</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow1_col7\" class=\"data row1 col7\" >0.52%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col0\" class=\"data row2 col0\" >3</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col1\" class=\"data row2 col1\" >lua</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col2\" class=\"data row2 col2\" >18150</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col3\" class=\"data row2 col3\" >17500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col4\" class=\"data row2 col4\" >5250</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col5\" class=\"data row2 col5\" >35000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col6\" class=\"data row2 col6\" >2956</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow2_col7\" class=\"data row2 col7\" >0.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col0\" class=\"data row3 col0\" >4</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col1\" class=\"data row3 col1\" >go</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col2\" class=\"data row3 col2\" >17989</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col3\" class=\"data row3 col3\" >16000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col4\" class=\"data row3 col4\" >6000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col5\" class=\"data row3 col5\" >40000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col6\" class=\"data row3 col6\" >25953</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow3_col7\" class=\"data row3 col7\" >7.38%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col0\" class=\"data row4 col0\" >5</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col1\" class=\"data row4 col1\" >haskell</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col2\" class=\"data row4 col2\" >17885</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col3\" class=\"data row4 col3\" >17500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col4\" class=\"data row4 col4\" >7500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col5\" class=\"data row4 col5\" >27000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col6\" class=\"data row4 col6\" >52</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow4_col7\" class=\"data row4 col7\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col0\" class=\"data row5 col0\" >6</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col1\" class=\"data row5 col1\" >python</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col2\" class=\"data row5 col2\" >17671</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col3\" class=\"data row5 col3\" >15000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col4\" class=\"data row5 col4\" >4000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col5\" class=\"data row5 col5\" >42400</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col6\" class=\"data row5 col6\" >28652</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow5_col7\" class=\"data row5 col7\" >8.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col0\" class=\"data row6 col0\" >7</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col1\" class=\"data row6 col1\" >matlab</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col2\" class=\"data row6 col2\" >17351</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col3\" class=\"data row6 col3\" >16000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col4\" class=\"data row6 col4\" >5250</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col5\" class=\"data row6 col5\" >37500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col6\" class=\"data row6 col6\" >5323</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow6_col7\" class=\"data row6 col7\" >1.51%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col0\" class=\"data row7 col0\" >8</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col1\" class=\"data row7 col1\" >ruby</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col2\" class=\"data row7 col2\" >16666</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col3\" class=\"data row7 col3\" >16000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col4\" class=\"data row7 col4\" >3672</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col5\" class=\"data row7 col5\" >35387</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col6\" class=\"data row7 col6\" >1069</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow7_col7\" class=\"data row7 col7\" >0.30%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col0\" class=\"data row8 col0\" >9</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col1\" class=\"data row8 col1\" >julia</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col2\" class=\"data row8 col2\" >16525</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col3\" class=\"data row8 col3\" >12500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col4\" class=\"data row8 col4\" >12500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col5\" class=\"data row8 col5\" >25000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col6\" class=\"data row8 col6\" >20</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow8_col7\" class=\"data row8 col7\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col0\" class=\"data row9 col0\" >10</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col1\" class=\"data row9 col1\" >kotlin</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col2\" class=\"data row9 col2\" >16079</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col3\" class=\"data row9 col3\" >15000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col4\" class=\"data row9 col4\" >5604</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col5\" class=\"data row9 col5\" >32500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col6\" class=\"data row9 col6\" >938</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow9_col7\" class=\"data row9 col7\" >0.27%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col0\" class=\"data row10 col0\" >11</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col1\" class=\"data row10 col1\" >perl</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col2\" class=\"data row10 col2\" >16001</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col3\" class=\"data row10 col3\" >14000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col4\" class=\"data row10 col4\" >5000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col5\" class=\"data row10 col5\" >37500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col6\" class=\"data row10 col6\" >2297</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow10_col7\" class=\"data row10 col7\" >0.65%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col0\" class=\"data row11 col0\" >12</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col1\" class=\"data row11 col1\" >cpp</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col2\" class=\"data row11 col2\" >15684</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col3\" class=\"data row11 col3\" >13500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col4\" class=\"data row11 col4\" >4000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col5\" class=\"data row11 col5\" >37500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col6\" class=\"data row11 col6\" >59278</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow11_col7\" class=\"data row11 col7\" >16.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col0\" class=\"data row12 col0\" >13</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col1\" class=\"data row12 col1\" >swift</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col2\" class=\"data row12 col2\" >15263</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col3\" class=\"data row12 col3\" >13000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col4\" class=\"data row12 col4\" >5250</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col5\" class=\"data row12 col5\" >35000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col6\" class=\"data row12 col6\" >2507</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow12_col7\" class=\"data row12 col7\" >0.71%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col0\" class=\"data row13 col0\" >14</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col1\" class=\"data row13 col1\" >objective_c</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col2\" class=\"data row13 col2\" >15020</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col3\" class=\"data row13 col3\" >13000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col4\" class=\"data row13 col4\" >4971</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col5\" class=\"data row13 col5\" >35417</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col6\" class=\"data row13 col6\" >232</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow13_col7\" class=\"data row13 col7\" >0.07%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col0\" class=\"data row14 col0\" >15</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col1\" class=\"data row14 col1\" >php</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col2\" class=\"data row14 col2\" >13789</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col3\" class=\"data row14 col3\" >12000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col4\" class=\"data row14 col4\" >3750</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col5\" class=\"data row14 col5\" >35000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col6\" class=\"data row14 col6\" >14382</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow14_col7\" class=\"data row14 col7\" >4.09%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col0\" class=\"data row15 col0\" >16</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col1\" class=\"data row15 col1\" >java</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col2\" class=\"data row15 col2\" >13465</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col3\" class=\"data row15 col3\" >12500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col4\" class=\"data row15 col4\" >3750</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col5\" class=\"data row15 col5\" >32500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col6\" class=\"data row15 col6\" >116525</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow15_col7\" class=\"data row15 col7\" >33.11%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col0\" class=\"data row16 col0\" >17</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col1\" class=\"data row16 col1\" >javascript</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col2\" class=\"data row16 col2\" >11971</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col3\" class=\"data row16 col3\" >11500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col4\" class=\"data row16 col4\" >3750</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col5\" class=\"data row16 col5\" >25000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col6\" class=\"data row16 col6\" >42940</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow16_col7\" class=\"data row16 col7\" >12.20%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col0\" class=\"data row17 col0\" >18</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col1\" class=\"data row17 col1\" >c_sharp</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col2\" class=\"data row17 col2\" >11564</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col3\" class=\"data row17 col3\" >10500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col4\" class=\"data row17 col4\" >3750</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col5\" class=\"data row17 col5\" >26611</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col6\" class=\"data row17 col6\" >44559</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow17_col7\" class=\"data row17 col7\" >12.66%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col0\" class=\"data row18 col0\" >19</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col1\" class=\"data row18 col1\" >visual_basic</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col2\" class=\"data row18 col2\" >11272</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col3\" class=\"data row18 col3\" >10416</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col4\" class=\"data row18 col4\" >4500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col5\" class=\"data row18 col5\" >21562</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col6\" class=\"data row18 col6\" >45</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow18_col7\" class=\"data row18 col7\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col0\" class=\"data row19 col0\" >20</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col1\" class=\"data row19 col1\" >delphi</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col2\" class=\"data row19 col2\" >10474</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col3\" class=\"data row19 col3\" >9000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col4\" class=\"data row19 col4\" >3750</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col5\" class=\"data row19 col5\" >20833</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col6\" class=\"data row19 col6\" >1206</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow19_col7\" class=\"data row19 col7\" >0.34%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col0\" class=\"data row20 col0\" >21</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col1\" class=\"data row20 col1\" >vba</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col2\" class=\"data row20 col2\" >9804</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col3\" class=\"data row20 col3\" >9000</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col4\" class=\"data row20 col4\" >3750</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col5\" class=\"data row20 col5\" >22500</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col6\" class=\"data row20 col6\" >668</td>\n",
       "                        <td id=\"T_56e7a924_3380_11ea_af77_701ce71031efrow20_col7\" class=\"data row20 col7\" >0.19%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x17a34e44b08>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "apply_style(data_pl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21, 8)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_pl.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_pl=data_pl[['pl_','percentage']].sort_values(by='percentage', ascending=False)\n",
    "data_pl.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "</style><table id=\"T_56ebeeee_3380_11ea_91f5_701ce71031ef\" ><thead>    <tr>        <th class=\"col_heading level0 col0\" >rank</th>        <th class=\"col_heading level0 col1\" >pl_</th>        <th class=\"col_heading level0 col2\" >percentage</th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow0_col0\" class=\"data row0 col0\" >1</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow0_col1\" class=\"data row0 col1\" >java</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow0_col2\" class=\"data row0 col2\" >33.11%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow1_col0\" class=\"data row1 col0\" >2</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow1_col1\" class=\"data row1 col1\" >cpp</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow1_col2\" class=\"data row1 col2\" >16.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow2_col0\" class=\"data row2 col0\" >3</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow2_col1\" class=\"data row2 col1\" >c_sharp</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow2_col2\" class=\"data row2 col2\" >12.66%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow3_col0\" class=\"data row3 col0\" >4</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow3_col1\" class=\"data row3 col1\" >javascript</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow3_col2\" class=\"data row3 col2\" >12.20%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow4_col0\" class=\"data row4 col0\" >5</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow4_col1\" class=\"data row4 col1\" >python</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow4_col2\" class=\"data row4 col2\" >8.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow5_col0\" class=\"data row5 col0\" >6</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow5_col1\" class=\"data row5 col1\" >go</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow5_col2\" class=\"data row5 col2\" >7.38%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow6_col0\" class=\"data row6 col0\" >7</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow6_col1\" class=\"data row6 col1\" >php</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow6_col2\" class=\"data row6 col2\" >4.09%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow7_col0\" class=\"data row7 col0\" >8</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow7_col1\" class=\"data row7 col1\" >matlab</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow7_col2\" class=\"data row7 col2\" >1.51%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow8_col0\" class=\"data row8 col0\" >9</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow8_col1\" class=\"data row8 col1\" >lua</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow8_col2\" class=\"data row8 col2\" >0.84%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow9_col0\" class=\"data row9 col0\" >10</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow9_col1\" class=\"data row9 col1\" >swift</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow9_col2\" class=\"data row9 col2\" >0.71%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow10_col0\" class=\"data row10 col0\" >11</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow10_col1\" class=\"data row10 col1\" >perl</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow10_col2\" class=\"data row10 col2\" >0.65%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow11_col0\" class=\"data row11 col0\" >12</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow11_col1\" class=\"data row11 col1\" >typescript</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow11_col2\" class=\"data row11 col2\" >0.52%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow12_col0\" class=\"data row12 col0\" >13</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow12_col1\" class=\"data row12 col1\" >delphi</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow12_col2\" class=\"data row12 col2\" >0.34%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow13_col0\" class=\"data row13 col0\" >14</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow13_col1\" class=\"data row13 col1\" >ruby</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow13_col2\" class=\"data row13 col2\" >0.30%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow14_col0\" class=\"data row14 col0\" >15</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow14_col1\" class=\"data row14 col1\" >kotlin</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow14_col2\" class=\"data row14 col2\" >0.27%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow15_col0\" class=\"data row15 col0\" >16</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow15_col1\" class=\"data row15 col1\" >vba</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow15_col2\" class=\"data row15 col2\" >0.19%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow16_col0\" class=\"data row16 col0\" >17</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow16_col1\" class=\"data row16 col1\" >rust</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow16_col2\" class=\"data row16 col2\" >0.14%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow17_col0\" class=\"data row17 col0\" >18</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow17_col1\" class=\"data row17 col1\" >objective_c</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow17_col2\" class=\"data row17 col2\" >0.07%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow18_col0\" class=\"data row18 col0\" >19</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow18_col1\" class=\"data row18 col1\" >haskell</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow18_col2\" class=\"data row18 col2\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow19_col0\" class=\"data row19 col0\" >20</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow19_col1\" class=\"data row19 col1\" >visual_basic</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow19_col2\" class=\"data row19 col2\" >0.01%</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                                <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow20_col0\" class=\"data row20 col0\" >21</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow20_col1\" class=\"data row20 col1\" >julia</td>\n",
       "                        <td id=\"T_56ebeeee_3380_11ea_91f5_701ce71031efrow20_col2\" class=\"data row20 col2\" >0.01%</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x17a3aea82c8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "data_pl['rank']=list(range(1,22))\n",
    "data_pl=data_pl[['rank','pl_','percentage']]\n",
    "#data_pl.style.format({\"percentage\":\"{:.2%}\"})\n",
    "data_pl.style.hide_index().format({\"percentage\":\"{:.2%}\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x648 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_pl=data_pl.sort_values(by='percentage')\n",
    "\n",
    "# Pie chart, where the slices will be ordered and plotted counter-clockwise:\n",
    "labels = data_pl['pl_']\n",
    "sizes = data_pl['percentage']\n",
    "#explode = (0, 0.1, 0, 0)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "\n",
    "fig1, ax1 = plt.subplots(figsize=(15, 9))\n",
    "ax1.pie(sizes, labels=labels, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "plt.title(f\"Programming Languages in China, {year}{month:02}\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Word Cloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from wordcloud import WordCloud\n",
    "wc=WordCloud()\n",
    "wc_dict = {}\n",
    "for index, row in data_pl.iterrows():\n",
    "    wc_dict[row['pl_']]=row['percentage']\n",
    "\n",
    "\n",
    "wc=wc.generate_from_frequencies(wc_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "wc_dict['c/c++']=0.33\n",
    "wc=wc.generate_from_frequencies(wc_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,6))\n",
    "plt.imshow(wc, interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020年1月\n"
     ]
    }
   ],
   "source": [
    "print(f'{year}年{month}月')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
